AI engineers

Description

At Sequoia Connect, we are a Talent-First Technology Ecosystem that redefines how elite professionals interact with the global digital landscape. We move beyond traditional models to act as a catalyst for the top 1% of global talent, connecting human potential with complex industrial execution. By joining our inner circle, you are not simply taking a position; you are aligning with a strategic partner dedicated to updating your "Human OS" and accelerating your growth through world-class, high-impact projects.

We are currently partnering with a global IT powerhouse that represents the connected world through innovative, customer-centric experiences. As a USD 6 billion organization and one of the top 7 IT service providers globally, our client empowers over 1,200 global customers—including several Fortune 500 companies—to "Rise™." With a massive network of 163,000+ professionals across 90 countries, they are at the absolute forefront of digital transformation, leveraging next-generation technologies such as 5G, AI, Blockchain, and Quantum Computing.

This is your chance to thrive in a workplace recognized as one of the most sustainable corporations in the world. You will join an environment that values innovation and societal impact, working on end-to-end digital transformation projects for global leaders. If you are a driven professional looking for global career opportunities and exposure to high-impact projects within an international network of expertise, this is where you belong.

We are currently searching for a AI engineers:

Responsibilities:

• Design and develop high-impact ML models to solve complex engineering problems in the semiconductor space.
• Build, train, and optimize deep learning models using NLP, Computer Vision, and Predictive Analytics.
• Implement advanced AI techniques including Agentic Frameworks, LangChain, and RAG (Retrieval-Augmented Generation).
• Execute data collection and preprocessing for both structured and unstructured data (numeric, images, videos, and documents) using Python.
• Perform feature engineering to transform raw data and improve model interpretability and performance.
• Deploy and integrate models using Kubernetes, Flask, Ray Serve, Azure DevOps, or ONNX.
• Monitor and evaluate model accuracy and robustness using rigorous statistical metrics.
• Maintain comprehensive documentation of model architecture and training processes for technical and non-technical stakeholders.
• Ensure all deployments adhere to ethical standards and data privacy regulations.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• 3+ years of professional experience in Machine Learning or Artificial Intelligence.
• Expertise in Python and PyTorch.
• Hands-on experience with cloud or on-premises compute for deep learning.
• Proven ability to handle unstructured data preprocessing (images, video, text).
• Practical knowledge of Model Deployment (Kubernetes, Flask, or cloud-based solutions).

Desired:

• PhD or relevant research experience.
• Experience in the semiconductor industry.
• Knowledge of Azure DevOps and ONNX for model interoperability.

Languages

• Advanced Oral English.
• Advanced Spanish.

Note:

• Fully remote.

If you meet these qualifications and are pursuing new challenges, start your application on our website to join an award-winning employer. Explore all our job openings | Sequoia Career’s Page: https://www.sequoia-connect.com/careers/

Requirements

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field.
• 3+ years of professional experience in Machine Learning or Artificial Intelligence.
• Expertise in Python and PyTorch.
• Hands-on experience with cloud or on-premises compute for deep learning.
• Proven ability to handle unstructured data preprocessing (images, video, text).
• Practical knowledge of Model Deployment (Kubernetes, Flask, or cloud-based solutions).
• PhD or relevant research experience.
• Experience in the semiconductor industry.
• Knowledge of Azure DevOps and ONNX for model interoperability.